Papers
Topics
Authors
Recent
Gemini 2.5 Flash
Gemini 2.5 Flash
194 tokens/sec
GPT-4o
7 tokens/sec
Gemini 2.5 Pro Pro
45 tokens/sec
o3 Pro
4 tokens/sec
GPT-4.1 Pro
38 tokens/sec
DeepSeek R1 via Azure Pro
28 tokens/sec
2000 character limit reached

A new fuzzy multi-attribute group decision-making method based on TOPSIS and optimization models (2311.15933v1)

Published 27 Nov 2023 in cs.AI

Abstract: In this paper, a new method based on TOPSIS and optimization models is proposed for multi-attribute group decision-making in the environment of interval-valued intuitionistic fuzzy sets.Firstly, by minimizing the sum of differences between individual evaluations and the overallconsistent evaluations of all experts, a new optimization model is established for determining expert weights. Secondly, based on TOPSIS method, the improved closeness index for evaluating each alternative is obtained. Finally, the attribute weight is determined by establishing an optimization model with the goal of maximizing the closeness of each alternative, and it is brought into the closeness index so that the alternatives can be ranked. Combining all these together, the complete fuzzy multi-attribute group decision-making algorithm is formulated, which can give full play to the advantages of subjective and objective weighting methods. In the end, the feasibility and effectiveness of the provided method are verified by a real case study.

Definition Search Book Streamline Icon: https://streamlinehq.com
References (25)
  1. Group decision making under multiple criteria: methods and applications, volume 281. Springer Science & Business Media, 2012.
  2. Fermatean fuzzy electre multi-criteria group decision-making and most suitable biomedical material selection. Artificial Intelligence in Medicine, 127:102278, 2022.
  3. Multi-criteria group decision-making for selection of green suppliers under bipolar fuzzy promethee process. Symmetry, 12(1):77, 2020.
  4. A multi-criteria intuitionistic fuzzy group decision making for supplier selection with topsis method. Expert systems with applications, 36(8):11363–11368, 2009.
  5. Zeshui Xu. On consistency of the weighted geometric mean complex judgement matrix in ahp. European journal of operational research, 126(3):683–687, 2000.
  6. Application of the entropy weight and topsis method in safety evaluation of coal mines. Procedia engineering, 26:2085–2091, 2011.
  7. Fraud vulnerability quantitative assessment of wuchang rice industrial chain in china based on ahp-ewm and ann methods. Food Research International, 140:109805, 2021.
  8. An integrated multi-criteria decision model to select sustainable construction projects under intuitionistic fuzzy conditions. Buildings, 13(4):848, 2023.
  9. Ting-Yu Chen. The inclusion-based topsis method with interval-valued intuitionistic fuzzy sets for multiple criteria group decision making. Applied Soft Computing, 26:57–73, 2015.
  10. A gra-based intuitionistic fuzzy multi-criteria group decision making method for personnel selection. Expert Systems with Applications, 38(9):11401–11405, 2011.
  11. A new design of the elimination and choice translating reality method for multi-criteria group decision-making in an intuitionistic fuzzy environment. Applied Mathematical Modelling, 37(4):1781–1799, 2013.
  12. Interval-valued intuitionistic fuzzy continuous weighted entropy and its application to multi-criteria fuzzy group decision making. Knowledge-Based Systems, 59:132–141, 2014.
  13. A new multi-criteria weighting and ranking model for group decision-making analysis based on interval-valued hesitant fuzzy sets to selection problems. Neural Computing and Applications, 27:1593–1605, 2016.
  14. A new approach to the determination of expert weights in multi-attribute group decision making. 2023.
  15. Lotfi A Zadeh. Fuzzy sets. Information and control, 8(3):338–353, 1965.
  16. Krassimir T Atanassov and S Stoeva. Intuitionistic fuzzy sets. Fuzzy sets and Systems, 20(1):87–96, 1986.
  17. Some comments on interval valued fuzzy sets. structure, 1(2), 1996.
  18. On hesitant fuzzy sets and decision. In 2009 IEEE international conference on fuzzy systems, pages 1378–1382. IEEE, 2009.
  19. Dual hesitant fuzzy sets. Journal of applied mathematics, 2012, 2012.
  20. Ronald R Yager. Pythagorean fuzzy subsets. In 2013 joint IFSA world congress and NAFIPS annual meeting (IFSA/NAFIPS), pages 57–61. IEEE, 2013.
  21. Interval valued intuitionistic fuzzy sets. Intuitionistic fuzzy sets: Theory and applications, pages 139–177, 1999.
  22. Deng-Feng Li. Closeness coefficient based nonlinear programming method for interval-valued intuitionistic fuzzy multiattribute decision making with incomplete preference information. Applied Soft Computing, 11(4):3402–3418, 2011.
  23. Approach to group decision making based on interval-valued intuitionistic judgment matrices. Systems Engineering-Theory & Practice, 27(4):126–133, 2007.
  24. Approach for aggregating interval-valued intuitionistic fuzzy information and its application to reservoir operation. Expert Systems with Applications, 38(7):9032–9035, 2011.
  25. H-J Zimmermann and P Zysno. Latent connectives in human decision making. Fuzzy sets and systems, 4(1):37–51, 1980.

Summary

We haven't generated a summary for this paper yet.